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Parallel Detection of Conversational Groups of Free-Standing People and Tracking of their Lower-Body Orientation

Marynel Vazquez, Aaron Steinfeld and Scott E. Hudson
Conference Paper, Carnegie Mellon University, Proc. of the 2015 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2015), September, 2015

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Abstract

Appropriate robot behavior in public, open spaces cannot occur without the ability to automatically detect conversational groups of free-standing people. To this end, we propose an alternating optimization procedure that estimates lower body orientations and detects groups of interacting people. The first task is achieved by tracking the direction of the lower body of the people in the scene based on their position, their head orientation, the location of objects of interest in their vicinity, and their groups. For the second task, we propose a new group detection algorithm based on F-formation detection. This method can reason about lower body orientation distributions, and generates soft group assignments for the orientation trackers. We evaluate the proposed approach on a publicly available dataset, and show that it can improve state-of- the art detection of non-interacting people without sacrificing group detection accuracy. This is particularly useful for robots since it provides more opportunities for starting interactions and can help estimate disengagement.

BibTeX Reference
@conference{Vazquez-2015-6025,
title = {Parallel Detection of Conversational Groups of Free-Standing People and Tracking of their Lower-Body Orientation},
author = {Marynel Vazquez and Aaron Steinfeld and Scott E. Hudson},
booktitle = {Proc. of the 2015 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2015)},
sponsor = {Disney Research Pittsburgh},
publisher = {IEEE},
school = {Robotics Institute , Carnegie Mellon University},
month = {September},
year = {2015},
address = {Pittsburgh, PA},
}
2017-09-13T10:38:34+00:00